Doctoral Thesis
Recent Submissions
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A multiscale approach to 3D-printed facades: energy, daylight, environmental impact
(2024)The building industry faces the challenge of transitioning to sustainable practices to contribute to climate change mitigation. At the same time, the sector is witnessing unprecedented opportunities thanks to digital design tools and fabrication technologies. This thesis explores the potential of 3D-printed facades as novel technologies to reduce the environmental impact of buildings. In construction, 3D printing has been mainly ...Doctoral Thesis -
Advancing Software Reliability from Code to Compilation
(2024)Software takes charge of every critical aspect of our modern society, including communication, finance, transportation, and many more. It is thus crucial to ensure the reliability of software systems. Yet, guaranteeing that non-trivial software systems are free of defects is extremely difficult, if not impossible. Consequently, modern software systems are full of bugs, such as security vulnerabilities, semantic bugs, performance issues, ...Doctoral Thesis -
Probing Gravity - Fundamental Aspects of Metric Theories and their Implications for Tests of General Relativity
(2024)Guided by the Einstein equivalence principle that identifies the phenomenon of gravitation as a manifestation of the dynamics of spacetime in contrast to a localizable force, we review and explore its consequences on formulating a theory of gravity. The resulting space of metric theories of gravity may address open conceptual and observational puzzles through a wealth of effects beyond general relativity, whose traces can be searched ...Doctoral Thesis -
Training and Certification of Neural Networks with Guarantees
(2024)Provable safety and trustworthiness guarantees are crucial for the safe adoption of neural network based systems in mission-critical applications. However, despite significant efforts, both training networks that satisfy such safety and trustworthiness properties and verifying that they do so remain open challenges. In this thesis, we tackle both of these challenges and demonstrate that they are closely intertwined. We present two novel ...Doctoral Thesis -
Actuarial Data Science: Insights from Pricing, Capital Modeling and CAT Bonds
(2024)Doctoral Thesis -
Chemical and mRNA-based Cellular Reprogramming to Muscle Progenitor Cells for the Treatment of Muscular Dystrophy
(2024)Muscular dystrophies encompass a group of genetic diseases with a wide spectrum of clinical severities. Duchenne muscular dystrophy (DMD) is the most common and debilitating form of dystrophy, causing progressive muscle wasting and premature death due to cardiorespiratory failure. DMD is triggered by mutations in the DMD gene that is needed to stabilize myofibers. Its absence causes perpetuating cycles of myofiber necrosis and muscle ...Doctoral Thesis -
Novel approaches for synthetic live biotherapeutic product production using immobilisation
(2024)The human gut microbiome plays an important role in health and disease and can easily be manipulated. This makes the gut microbiome a promising target for therapeutic modulation. Groups of bacteria, also called consortia, are a means to specifically enrich the gut microbiome composition with potential missing beneficial functions. However, efficient production of these synthetic consortia is challenging. The current production strategy ...Doctoral Thesis -
Navigating collaboration for innovation both within and across organizational boundaries: An interaction-centric perspective
(2024)Innovation is crucial for firms’ long-term success, and collaboration within and across organizational boundaries is crucial for innovation, making it important to understand collaboration demands and their navigation. To do so, scholars suggested taking a holistic approach by attending to interactions between relevant elements. Yet, while collaboration elements like tensions, challenges, and success-factors have been described, there ...Doctoral Thesis -
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Agile and Efficient Inference of Quantized Neural Networks
(2024)The rapid proliferation of the internet of things (IoT) has coincided with a revolution in machine learning, driven by deep learning-based algorithms. At the intersection of these developments, smart sensing systems aim to integrate sensing, deep learning-based interpretation of the captured data and reaction to the results of the processing. As battery-powered IoT sensor nodes operate under stringent power, memory and compute resource ...Doctoral Thesis -
Lagrangian Cobordisms in Liouville Manifolds
(2024)The following thesis is based on the two articles and divided into two parts accordingly. The first part defines Lagrangian cobordisms in Liouville manifolds between non-compact Lagrangian submanifolds. Biran and Cornea showed that Lagrangian cobordisms between compact Lagrangian submanifolds can be used to study the triangulated structure of the derived Fukaya category. This statement is transferred to the non-compact setting to study ...Doctoral Thesis -
Measuring and modeling time use patterns in Switzerland
(2024)As part of this dissertation, a novel survey methodology was developed for the collection of rich, longitudinal travel, time use, and expenditure data, leveraging the opportunities offered by both passive GPS tracking technology and time use diaries. Based on these data, patterns and preferences related to paid work, leisure, and other activities that comprise our everyday life were evaluated. Activities performed inside and outside of ...Doctoral Thesis -
Single-Layer Transition-Metal Dichalcogenides Through Vapor-Liquid-Solid Chemical Vapor Deposition
(2024)Doctoral Thesis -
A Software Framework for Bayesian Uncertainty Quantification, Optimization, and Reinforcement Learning
(2024)In this doctoral thesis, we present a high-performance computing framework tailored for stochastic optimization, Bayesian uncertainty quantification, and (inverse) reinforcement learning. The development of this framework has facilitated numerous applications across various domains: optimization and Bayesian uncertainty studies in biology and epidemiology, reinforcement learning techniques for drag reduction in a channel-flow, and inferring ...Doctoral Thesis -
Advancing Global Parameter Estimation of Gravitational Waves Recorded by LISA
(2024)Doctoral Thesis -
Denoising Monte Carlo Renderings: a Sub-Pixel Exploration with Deep Learning
(2024)Doctoral Thesis -
New graph learning approaches for exploring gene and protein function
(2024)Graphs serve as a universal tool for modeling intricate systems of interacting components, making them especially well-suited for representing knowledge on biological processes, including disease pathways, and complex biological molecules like proteins. In addition to providing a mathematical framework for representing biological components and their interactions, the use of graphs unlocks a suite of learning methods to extract insights ...Doctoral Thesis -
Ultrasound-driven Ciliated Microrobotic Systems for Biomedical Applications
(2024)Doctoral Thesis